Collaborative research: Neural and cognitive strengthening of conceptual knowledge and reasoning in classroom-based spatial education

合作研究：基于课堂的空间教育中概念知识和推理的神经和认知强化

• 批准号: 1661088
• 负责人: David Kraemer
• 金额: $ 32.27万
• 依托单位: Dartmouth College
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-15 至 2023-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1661088&HistoricalAwards=false
• 关键词: Collaborative; research; Neural; cognitive; strengthening

Spatial thinking is a powerful driver of success in the STEM classroom and spatial thinking is a major predictor of future STEM success in the workforce. The brain systems that support spatial thinking have been well mapped by neuroscience to allow clear interpretation of new brain-imaging data. Recent advances in tools used to analyze brain activity allow detection of changes in the brains of students that signify accurate learning of STEM concepts. This advance may open a window onto biomarkers of precisely the type of learning that is the goal of educators. Using these new brain analysis methods, this project, a collaboration involving researchers from James Madison University, Georgetown University, Northwestern University, and Dartmouth College, will investigate how changes in the spatial thinking network support learning of specific STEM concepts, and how changes in the classroom can facilitate changes in the brain related to spatial thinking. This cross-disciplinary project brings together experts in geoscience classroom education, spatial cognition, and the neural bases of learning and reasoning. This team is committed to bridging the conspicuous gap between the laboratory and the high school classroom. A confluence of advances in neuroimaging, and the research team's partnership with Virginia school systems make this effort timely and tractable. Identifying possible effects of sex and STEM-related anxieties on conceptual learning in the brain, and testing the effectiveness of spatial education for reducing disparities, this research will point to critical targets for intervention. The project is funded by the EHR Core Research (ECR) program, which supports work that advances the fundamental research literature on STEM learning.This project seeks to understand the neural mechanisms of spatial learning, to advance of spatial education, and to identify factors that affect disparities in STEM learning and participation. The research team will collect functional magnetic resonance imaging (fMRI) and behavioral data from students before and after learning in a high school geoscience course that uses a novel spatially-based curriculum to teach STEM concepts and spatial reasoning. Pilot data on this spatial curriculum have begun to characterize the underlying cognitive and neural mechanisms at work, and show promising effects of transfer to STEM problem solving and core measures of spatial ability. Consistent with methods that have demonstrated success in the lab (but not yet the classroom), the research team will use multivariate neural representations of a group of highly experienced and specially trained teachers as an expert standard to determine neural markers of students? conceptual knowledge and spatial reasoning. Leveraging recent multivariate pattern analysis (MVPA) and machine-learning advances in brain imaging, the team will compare the neural patterns of students before and after learning to test for a trajectory that moves students closer to expert representations. This project will also test, for the first time, whether it is possible to compare different curricula based on how much they strengthen the representation of a concept in the brain. Similarly, this work will test whether spatial education leads students to engage spatial brain resources for STEM-related reasoning, and seek to compare curricula on this basis. The project will test whether neural data add predictive value to traditional testing (e.g. conventional unit tests) for subsequent retention of conceptual knowledge and spatial reasoning. Assessments of STEM-related anxieties (e.g., math and spatial anxiety) and analyses of sex-related effects on cognitive and neural outcomes will newly characterize factors that influence disparities in STEM learning and participation.

空间思维是STEM课堂上取得成功的强大驱动力，而空间思维是未来STEM在劳动力市场取得成功的主要预测因素。神经科学已经很好地描绘了支持空间思维的大脑系统，以便对新的大脑成像数据进行清晰的解释。用于分析大脑活动的工具的最新进展使人们能够检测到学生大脑的变化，这意味着准确地学习STEM概念。这一进展可能会为了解教育工作者所追求的学习类型的生物标记物打开一扇窗。使用这些新的大脑分析方法，这个项目由来自詹姆斯·麦迪逊大学、乔治城大学、西北大学和达特茅斯学院的研究人员合作，将调查空间思维网络的变化如何支持特定STEM概念的学习，以及课堂上的变化如何促进与空间思维相关的大脑变化。这个跨学科的项目汇集了地球科学课堂教育、空间认知以及学习和推理的神经基础方面的专家。这个团队致力于弥合实验室和高中教室之间的明显差距。神经成像技术的进步，以及研究团队与弗吉尼亚学校系统的合作，使这一努力及时且易于处理。这项研究确定了性和STEM相关焦虑对大脑概念学习的可能影响，并测试了空间教育对减少差异的有效性，这项研究将指出干预的关键目标。该项目由EHR核心研究(ECR)计划资助，该计划支持推进STEM学习基础研究文献的工作。该项目旨在了解空间学习的神经机制，促进空间教育，并确定影响STEM学习和参与差异的因素。研究小组将收集学生在高中地球科学课程学习前后的功能磁共振成像(FMRI)和行为数据，该课程使用一种新的基于空间的课程来教授STEM概念和空间推理。关于这一空间课程的试点数据已经开始描述起作用的潜在认知和神经机制，并显示出迁移到STEM问题解决和空间能力核心衡量标准的良好效果。与在实验室(但还没有在课堂上)证明成功的方法一致，研究团队将使用一组经验丰富和受过专门培训的教师的多元神经表征作为专家标准来确定学生的神经标记？概念知识和空间推理。利用最新的多变量模式分析(MVPA)和机器学习在脑成像方面的进展，该团队将比较学生学习前后的神经模式，以测试使学生更接近专家代表的轨迹。该项目还将首次测试，是否可以根据不同课程在多大程度上加强大脑中的概念表征来比较它们。同样，这项工作将测试空间教育是否会导致学生利用空间大脑资源进行STEM相关推理，并在此基础上寻求比较课程。该项目将测试神经数据是否为传统测试(例如传统单元测试)增加预测价值，以便随后保留概念知识和空间推理。对STEM相关焦虑(例如，数学和空间焦虑)的评估，以及对性别对认知和神经结果的影响的分析，将重新表征影响STEM学习和参与差异的因素。

项目成果

Using the force: STEM knowledge and experience construct shared neural representations of engineering concepts

• DOI: 10.1038/s41539-020-0065-x
• 发表时间: 2020-01-01
• 期刊: NPJ SCIENCE OF LEARNING
• 影响因子: 4.2
• 作者: Cetron, Joshua S.;Connolly, Andrew C.;Kraemer, David J. M.
• 通讯作者: Kraemer, David J. M.

Mental models use common neural spatial structure for spatial and abstract content

• DOI: 10.1038/s42003-019-0740-8
• 发表时间: 2020-01-09
• 期刊: COMMUNICATIONS BIOLOGY
• 影响因子: 5.9
• 作者: Alfred, Katherine L.;Connolly, Andrew C.;Kraemer, David J. M.
• 通讯作者: Kraemer, David J. M.

Decoding individual differences in STEM learning from functional MRI data

• DOI: 10.1038/s41467-019-10053-y
• 发表时间: 2019-05-02
• 期刊: NATURE COMMUNICATIONS
• 影响因子: 16.6
• 作者: Cetron, Joshua S.;Connolly, Andrew C.;Kraemer, David J. M.
• 通讯作者: Kraemer, David J. M.

Individual differences in encoded neural representations within cortical speech production network

皮质语音产生网络中编码神经表示的个体差异

• DOI: 10.1016/j.brainres.2019.146483
• 发表时间: 2020
• 期刊: Brain Research
• 影响因子: 2.9
• 作者: Alfred, Katherine L.;Hayes, Justin C.;Pizzie, Rachel G.;Cetron, Joshua S.;Kraemer, David J.M.
• 通讯作者: Kraemer, David J.M.

Developing a neurally informed ontology of creativity measurement

• DOI: 10.1016/j.neuroimage.2020.117166
• 发表时间: 2020-07
• 期刊: NeuroImage
• 影响因子: 5.7
• 作者: Yoed N. Kenett;David J. M. Kraemer;Katherine L. Alfred;Griffin A. Colaizzi;Robert A. Cortes;Adam E. Green